Anatomy Segmentation of Breast Ultrasound images

Detalhes bibliográficos
Autor(a) principal: António Mesquita dos Santos Marques Carreiro
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/123037
Resumo: Breast cancer is one of the most common cancers in women, affecting hundreds of women. Even though the detection of cancer has been largely studied, the decision of which strategy to take concerning oncoplastic surgery still relies almost exclusively on the surgeon's perception of post-surgical aesthetic result, which sometime leads to unsatisfactory outcomes. In order to empower the patients on the joint decision process there needs to exist a better communication between the parts. This can be achieved by developing medical grade 3D models of the breast and explaining better the surgical options and their results. In order to obtain such models, some effort has been made concerning multi-modality radiological imaging combination. This line of research has yet to mature. In turn, the modality alignment requires accurate landmarks to be produced. 2D Ultrasound imaging has not been sufficiently studied for multimodal registration due to the image characteristics and thus, landmark segmentation is of utmost importance. This task can be challenging since US data presents high specular noise levels and the presence of some tissues alters the perception of other tissues. Objectives: ● Study and evaluation of different techniques for anatomical landmark segmentation, such as Skin, Fat and Glandular tissue, Lesions (masses and cysts), Pectoral muscle; ● Development of Ultrasound segmentation methods for acquiring landmarks; ● Evaluation of the developed methods with manual annotations and comparison of results with the current algorithm alternatives.
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spelling Anatomy Segmentation of Breast Ultrasound imagesEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineeringBreast cancer is one of the most common cancers in women, affecting hundreds of women. Even though the detection of cancer has been largely studied, the decision of which strategy to take concerning oncoplastic surgery still relies almost exclusively on the surgeon's perception of post-surgical aesthetic result, which sometime leads to unsatisfactory outcomes. In order to empower the patients on the joint decision process there needs to exist a better communication between the parts. This can be achieved by developing medical grade 3D models of the breast and explaining better the surgical options and their results. In order to obtain such models, some effort has been made concerning multi-modality radiological imaging combination. This line of research has yet to mature. In turn, the modality alignment requires accurate landmarks to be produced. 2D Ultrasound imaging has not been sufficiently studied for multimodal registration due to the image characteristics and thus, landmark segmentation is of utmost importance. This task can be challenging since US data presents high specular noise levels and the presence of some tissues alters the perception of other tissues. Objectives: ● Study and evaluation of different techniques for anatomical landmark segmentation, such as Skin, Fat and Glandular tissue, Lesions (masses and cysts), Pectoral muscle; ● Development of Ultrasound segmentation methods for acquiring landmarks; ● Evaluation of the developed methods with manual annotations and comparison of results with the current algorithm alternatives.2019-09-192019-09-19T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/10216/123037TID:202389855engAntónio Mesquita dos Santos Marques Carreiroinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T12:32:01Zoai:repositorio-aberto.up.pt:10216/123037Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:22:06.819125Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Anatomy Segmentation of Breast Ultrasound images
title Anatomy Segmentation of Breast Ultrasound images
spellingShingle Anatomy Segmentation of Breast Ultrasound images
António Mesquita dos Santos Marques Carreiro
Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
title_short Anatomy Segmentation of Breast Ultrasound images
title_full Anatomy Segmentation of Breast Ultrasound images
title_fullStr Anatomy Segmentation of Breast Ultrasound images
title_full_unstemmed Anatomy Segmentation of Breast Ultrasound images
title_sort Anatomy Segmentation of Breast Ultrasound images
author António Mesquita dos Santos Marques Carreiro
author_facet António Mesquita dos Santos Marques Carreiro
author_role author
dc.contributor.author.fl_str_mv António Mesquita dos Santos Marques Carreiro
dc.subject.por.fl_str_mv Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
topic Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
description Breast cancer is one of the most common cancers in women, affecting hundreds of women. Even though the detection of cancer has been largely studied, the decision of which strategy to take concerning oncoplastic surgery still relies almost exclusively on the surgeon's perception of post-surgical aesthetic result, which sometime leads to unsatisfactory outcomes. In order to empower the patients on the joint decision process there needs to exist a better communication between the parts. This can be achieved by developing medical grade 3D models of the breast and explaining better the surgical options and their results. In order to obtain such models, some effort has been made concerning multi-modality radiological imaging combination. This line of research has yet to mature. In turn, the modality alignment requires accurate landmarks to be produced. 2D Ultrasound imaging has not been sufficiently studied for multimodal registration due to the image characteristics and thus, landmark segmentation is of utmost importance. This task can be challenging since US data presents high specular noise levels and the presence of some tissues alters the perception of other tissues. Objectives: ● Study and evaluation of different techniques for anatomical landmark segmentation, such as Skin, Fat and Glandular tissue, Lesions (masses and cysts), Pectoral muscle; ● Development of Ultrasound segmentation methods for acquiring landmarks; ● Evaluation of the developed methods with manual annotations and comparison of results with the current algorithm alternatives.
publishDate 2019
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